The present disclosure relates generally to diagnosing sleep-disordered breathing (SDB) non-invasively by analyzing physiologic data.
Sleep-disordered breathing (SDB) describes a group of respiratory disorder during sleep. Obstructive sleep apnea (OSA), the most common such disorder, is characterized by periodic cessations of breathing during sleep due to intermittent airway obstructions. OSA is a frequently undiagnosed condition affecting millions of individuals worldwide, and it is associated with increased morbidity and mortality.
Conventional diagnosis technologies for sleep-disordered breathing require overnight monitoring of a patient in a specially equipped sleep laboratory. Standard polysomnographic recordings in a sleep laboratory typically include electro-encephalography (EEG), electro-oculography (EOG), electromyography (EMG), airflow, respiratory efforts, SpO2, body position, and electrocardiography (ECG), which are often expensive and inconvenient to use. Less costly, easier or home-based, and reliable techniques are therefore desirable for detecting SDB in high-risk population.